Is the Variable X—ray Source in M82 due to Gravitational Lensing？

1 INTRODUCTIONObservations of the most famous starburst galaxy M82 with the High-Resolution Cameraon board the Chandra X-Ray Observatory, showed that there are nine sources in the celltral11 x 11 region, but no son-roe was detected at the galactic center (Matsumoto et al. 2001).Comparing the observations on 1999 October 28 and those on 2000 January 20, the authorsfound an extremely large time variability of the source CXO M82 J095550.2 694047, which islocated gll away from the galact…     

遥感技术与美国的人口普查

引言 D.布鲁金尼的论文《可用空间时代技术进行更精确的人口普查》提出了一些有趣的问题。我们为能够在《摄影测量工程和遥感》杂志上看到这篇有关遥感在社会科学领城内的应用的论文而高兴。我们认为只有了解人口普查数据的多种用途之后,再来检验那些改进人口普查的方法才是合适的,众所周知,每十年一次的人口普查数据的精度和完备性并不是没有缺点的。无疑地,许多人口普查人员将首先承认,每次由点数     

Formation Pressure Evaluation Method for Single Well

The paper deals with the methods of formation pressure evaluation for a single well by using the very common ac-cepted parameters, such as drilling exponent , and flowline temperature , etc. which is part of compiling the end well report.     

STUDY ON BEIJING''''S EMERGING MOBILE COMMUNICATION INDUSTRIAL CLUSTER AND ITS POLICY IMPLICATIONS

1INTRODUCTIONClusters,definedasgeographicallyproximategroupsofinterconnectedcompaniesandassociatedinstitutionsinparticularfields,linkedbycommonalitiesandcomple-mentarities(PORTER,2000),havearousedanintenseinterestofurbanandregionalplanningresearchersandpolicymakersoverthepastdecades.Itiswidelyrecog-nizedthatclusterscanpromoteproductivityandinno-vation,developlocalcompetitiveadvantages.Popular-izedbyMichaelPORTERinhisbook“TheCompetitiveAdvantageofNationsin1990,theclusterisnotanewcon…     

Late Cretaceous-Paleogene Palynostratigraphy from the Arkhara-Boguchan Brown Coal Mine of Zeya-Bureya Depression, Russia

1IntroductionThe Arkhara-Boguchan brown coal mine is lo-cated in the western Arkhara depression,southeast-ern part of the Zea-Bureya Basin (Fig.1). Late Creta-ceous-Paleogene coal-bearing strata are well out-cropped at the Arkhara-Boguchan quarry. It contains four coal-bearing beds (in descending order): “Ve-likan”, “Promezhutochny”,“Dvoinoy”and “Nyzhny”, and composed of three sedimentary cycles (Fig.2). The lower cycle can be divided into two sub-cycles:the lowest sub-cycle is …     

APPLICATION OF GEOGRAPHICAL PARAMETER DATABASE TO ESTABLISHMENT OF UNIT POPULATION DATABASE

Now GIS is turning into a good tool in handling geographical, economical, and population data, so we can obtain more and more information from these data. On the other hand, in some cases, for a calamity, such as hurricane, earthquake, flood, drought etc., or a decision-making, such as setting up a broadcasting transmitter, building a chemical plant etc., we have to evaluate the total population in the region influenced by a calamity or a project. In this paper, a method is put forward to evaluate the population in such special region. Through exploring the correlation of geographical parameters and the distribution of people in the same region by means of quantitative analysis and qualitative analysis, unit population database (1km× 1km) is established. In this way, estimating the number of people in a special region is capable by adding up the population in every grid involved in this region boundary. The geographical parameters are obtained from topographic database and DEM database on the scale of     

On the Spectral Index－Flux Density Relation for Large Samples of Radio Sources

We present new statistical results on the spectral index-flux density relation for large samples of radio sources using archival data of the most sensitive surveys, such as 6C, Miyun, WENSS, B3, NVSS, GB87. Instrumental selection effects and the completeness of the catalogs are discussed. Based on the spectral indices calculated for about 200 000 sources from the WENSS (327 MHz) and NVSS (1.4 GHz) catalogs, we obtained (1) The median spectral index increases from amed --0.9 toαmed --0.8 (Svαvα), while S327 flux densities decrease from 0.1 Jy down to 25mJy. The median spectral indices nearly show no variation within the error bars when the flux density is larger than 0.1 Jy. (2) A dependence of the fraction of ultra-steep spectrum sources (USS, -1.5 <α<-1.0), steep spectrum sources (SSS, -1.0 <α< -0.5) and flat spectrum sources (FSS, -0.5≤α≤0.0) is partly responsible for the spectral flattening. Another contribution to the spectral flattening comes from the variation of αmed of steep spectrum so